In the past twenty years there has been an explosion in the amount of information made available to professionals in all fields. The reasons for this explosion in the amount of information made available to professionals are many. Key among the reasons for the explosion in the information made available to professionals are more sophisticated and accurate testing techniques. Such sophisticated and accurate testing techniques produce numerical measurements quantifying multiple parameters. Just a few years ago, many of the numerical measurements now provided to professionals were unavailable. Because numerical measurements are easily transmitted using computer-based communication there has been a tremendous increase in the amount of numerical information provided to professionals in many fields of endeavor.
An unfortunate consequence of making large amounts of information available to professionals is that the finite capacity of human beings to absorb and to contextualize may be exceeded. When the finite capacity of a human being to absorb and contextualize information is exceeded there may be several adverse consequences. For example, important data may become buried in unimportant data. Some important data may even be inadvertently ignored. Signals of changes in data reflecting trends in the measurement of important parameters are missed. Valuable time is spent reviewing inconsequential background data. Missing key data or signals in changes in data masks the need to research the reasons for data distortions or data anomalies in key indicators.
One example illustrating the problem of exceeding the finite capacity of human beings to absorb and contextualize information is in the treatment of patients by health care providers. Health care providers, particularly medical doctors, are given complex patient reports to quickly read, properly analyze, and then, based on their analysis of the data presented, prescribe a course of patient treatment or therapy. Example of such reports appear in FIGS. 1A, 1B, and 1C. Shown therein are multiple pages of an exemplary array of medical information for a woman diagnosed with breast cancer. A busy oncologist may be called upon to review forty or fifty of such arrays of medical information each day. Despite the effort spent reviewing each chart to look for variances from a norm or to spot trends, the complex nature of a medical chart and physician (user) fatigue may cause key information, such as a variance from a norm or a data anomaly, to be missed. The consequences of missing key items of data, particularly in a health care situation, can be extremely dangerous or even fatal.
In addition to spotting a data variance from a norm, there is also a need to prioritize the information displayed to provide the professional reviewing the data with an indication of what may be the most critical of the variances from a norm and what as opposed to other variances from a norm that may be less critical. Further, if information is available regarding generally accepted interventions or therapy needed to respond to one or more variances from a norm, information regarding such generally accepted variances can be displayed.
Again, the treatment of patients by health care providers provides an illustrative example of a need in the art. Once a medical doctor reviews the report shown in FIGS. 1A, 1B, and 1C there may be a need for drug therapy intervention. If the patient has a unique condition or if the attending physician is not familiar with the use of some medications, the attending physician may have to consult a reference to select the correct medication. Thus, the need remains for a system which can quickly recognize the variance from a norm or anomaly in reported data, provide more detailed data explaining the variance from the norm or the data anomaly, and then provide a list of generally accepted drug therapy interventions. Further, such system should also be able to warn the medical doctor of any potential adverse consequences from recommended interventions such as drug interactions.
Accordingly, there remains in the art a need for a system and method which will aggregate and prioritize data relating to a particular subject. Such aggregation and prioritization of the data relating to a particular subject will enable spotting data showing either a data variance from a norm or a data anomaly. Once spotted, the user should be able to focus attention on the data variance or the data anomaly to obtain additional information about the data variance or the data anomaly. Further, there is also a need for displaying the intervention recommended, if any, in response to the variance from a norm or the anomaly. The observer of a recommended intervention should then have access to additional information further explaining the potential consequences of a recommended intervention. In addition, the observer should be able to aggregate multiple sets of data; for example, from multiple patients to enable the discovery of information characteristics of trends found in a larger universe of information revealed by observing multiple sets of data.